Dealing with small samples in disability research: Do not fret, Bayesian analysis is here.

IF 1.9 4区医学 Q3 PSYCHOLOGY, CLINICAL

Rehabilitation Psychology Pub Date : 2024-08-22 DOI:10.1037/rep0000579

Karyssa A Courey, Felix Y Wu, Frederick L Oswald, Claudia Pedroza

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引用次数: 0

Abstract

Purpose/objective: Small sample sizes are a common problem in disability research. Here, we show how Bayesian methods can be applied in small sample settings and the advantages that they provide.

Method/design: To illustrate, we provide a Bayesian analysis of employment status (employed vs. unemployed) for those with disability. Specifically, we apply empirically informed priors, based on large-sample (N = 95,593) July 2019 Current Population Survey (CPS) microdata to small subsamples (average n = 26) from July 2021 CPS microdata, defined by six specific difficulties (i.e., hearing, vision, cognitive, ambulatory, independent living, and self-care). We also conduct a sensitivity analysis, to illustrate how various priors (i.e., theory-driven, neutral, noninformative, and skeptical) impact Bayesian results (posterior distributions).

Results: Bayesian findings indicate that people with at least one difficulty (especially ambulatory, independent living, and cognitive difficulties) are less likely to be employed than people with no difficulties.

Conclusions/implications: Overall, results suggest that Bayesian analyses allow us to incorporate known information (e.g., previous research and theory) as priors, allowing researchers to learn more from small sample data than when conducting a traditional frequentist analysis. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

查看原文本刊更多论文

处理残疾研究中的小样本问题：别担心，贝叶斯分析法就在这里。

目的/目标：小样本量是残疾研究中的一个常见问题。在此，我们将展示如何在小样本环境中应用贝叶斯方法，以及贝叶斯方法所带来的优势：为了说明这一点，我们对残疾人的就业状况（就业与失业）进行了贝叶斯分析。具体来说，我们将基于 2019 年 7 月当前人口调查（CPS）微观数据的大样本（N = 95,593 个）经验先验应用于 2021 年 7 月当前人口调查微观数据的小样本（平均 n = 26 个），小样本由六种特定困难（即听力、视力、认知、行动能力、独立生活能力和自理能力）定义。我们还进行了敏感性分析，以说明各种先验（即理论驱动型、中性、非信息型和怀疑型）对贝叶斯结果（后验分布）的影响：结果：贝叶斯研究结果表明，至少有一种困难（尤其是行动不便、独立生活和认知困难）的人比没有困难的人更不可能就业：总体而言，研究结果表明，贝叶斯分析法允许我们将已知信息（如以前的研究和理论）作为先验信息，从而使研究人员能够从小规模样本数据中学到比进行传统频数分析更多的东西。(PsycInfo Database Record (c) 2024 APA, 版权所有）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Rehabilitation Psychology Multiple-

CiteScore

4.80

自引率

7.40%

发文量

期刊介绍： Rehabilitation Psychology is a quarterly peer-reviewed journal that publishes articles in furtherance of the mission of Division 22 (Rehabilitation Psychology) of the American Psychological Association and to advance the science and practice of rehabilitation psychology. Rehabilitation psychologists consider the entire network of biological, psychological, social, environmental, and political factors that affect the functioning of persons with disabilities or chronic illness. Given the breadth of rehabilitation psychology, the journal"s scope is broadly defined.